{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introducing...mander"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from mander import districts, metrics, utils\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Single District Scores "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load geojson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "myDistrict = districts.District('test/data/CD_CA_24.geojson')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Look at shapes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "myDistrict.gdf.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get a score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "metrics.calculateReock(myDistrict)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multi-district Scores "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load geojson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fname = 'test/data/MN_Senate_2017.geojson'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "myDistrict = districts.District(fname)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Look at shapes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x107750710>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SZ9/+An+5/Q42b97MCSecgEqlwuf1Nqg7+Iwryc/LYfr06WHfd9qxYwdnnz2eb1f+zK1v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\nqeORKYjRhgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107738910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "myDistrict.gdf.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get some scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "reocks = metrics.calculateReock(myDistrict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  4.,   2.,   1.,   8.,  10.,  13.,   8.,  11.,   6.,   4.]),\n",
       " array([ 0.24700892,  0.28376681,  0.3205247 ,  0.35728259,  0.39404048,\n",
       "         0.43079836,  0.46755625,  0.50431414,  0.54107203,  0.57782992,\n",
       "         0.6145878 ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dwBnA84DHAB9L8rEB5t3Impmq6jPMsU7z7sl/Hjhpxe0TZ/d9nyz/UvMS4PyqemA7Y0fI\nRVV9cfbf/wbew/L/Wg2SaUWG64GTk5yw3bEDZRpznZ4FvCvJfwEvAf42yflbHDtUpr+ZZVrUOm0p\nV1V9/buH3KrqWuDosZ9TG2Qa8zl1P/D+qvpWVX0F+DfgGVscO3Sm+dZpzl8eHMX3fnmwm+VfHpy2\napuTgE8DZ2137LyXjrmOAx47u/4Y4KPAzw6U6akrrp8B3LfIteqYabR1WrX95XzvF6+jrdMGmRay\nTtv4+e1Zcf1M4J6x12qDTGO+9k4FPjDb9jjgk8DTRl6n9TLNtU5zHa6pdT4IleQ3l79clwB/ApzA\n8t5WgAer6sz1xs6To89cwB7gPVk+DcMu4J1Vdd1AmX4pySuB/wP+F3jpRmPHzMS46/R9QzYbO2Ym\nFrRO28j1kiS/BTzI8s/vVzYaO2YmRnxOVdVdSd4P3AY8BFxSVXcCjLVO62VK8hTmWCc/DCVJDfPP\n/0lSwyx5SWqYJS9JDbPkJalhlrwkNcySl6SGWfKS1DBLXpIa9v84aCQWsGtrowAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e9fb050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(reocks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save your results back to geojson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "metrics.scoresToGeojson(myDistrict, 'polsbypopper', 'test/data/MN_Senate_2017_polsby.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "metrics.scoresToGeojson(myDistrict, 'reock', 'test/data/MN_Senate_2017_reock.geojson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
